Measurment of Arm Swing Asymmetry Using Video-based Motion Analysis and Accelerometery
Campbell, Nancy Marie
Area of Honors:
Bachelor of Science
Stephen Jacob Piazza, Thesis Supervisor Stephen Jacob Piazza, Honors Advisor Jinger S. Gottschall, Faculty Reader
arm swing accelerometers video-based motion analysis
For chronic and progressive illnesses, such as Parkinson’s disease, early disease detection can be crucial in delaying the advancement of symptoms and preventing early death. Recent research has suggested the use of arm swing asymmetry as one criterion to be used in Parkinson’s diagnosis. It is unknown, however, which method is the most sensitive detector of arm swing asymmetry. In this study, a perturbation, in the form of unequal wrist weights, was used to induce arm swing asymmetry in ten normal, healthy college students. Arm motion was detected using video-based motion analysis and accelerometers, and arm swing was quantified as excursion of the wrist, forearm accelerations computed from video-based motion analysis, and forearm accelerations obtained from accelerometers. Approximately one and a half strides of steady-state walking data were analyzed in each trial. The areas under receiver operator characteristic curves indicated that accelerations from marker data were the most sensitive detectors of arm swing changes in response to the applied perturbations. Analyses of variance and post-hoc mean comparisons showed that increasing the mass added to the wrist resulted in decreases in arm swing and that women had larger arm swings than men.